Time-optimal trajectory optimization of serial robotic manipulator with kinematic and dynamic limits based on improved particle swarm optimization

• Published in: International journal of advanced manufacturing technology Vol. 120; no. 1-2; pp. 1253 - 1264
• Main Authors: Yang, Yu, Xu, Hong-ze, Li, Shao-hua, Zhang, Ling-ling, Yao, Xiu-ming
• Format: Journal Article
• Language: English
• Published: London Springer London 01.05.2022; Springer Nature B.V
• Subjects: Algorithms; Angular acceleration; Angular velocity; CAE) and Design; Computer-Aided Engineering (CAD; Continuity (mathematics); Controllers; Convergence; Engineering; Industrial and Production Engineering; Industrial robots; Interpolation; Kinematics; Manipulators; Mechanical Engineering; Media Management; Motion control; Optimization; Original Article; Particle swarm optimization; Polynomials; Robot arms; Robotics; Trajectory optimization; Trigonometric functions; Second-order continuous polynomial interpolation function; Particle swarm optimization with cosine-decreasing weight; Kinematic and dynamic limits; Time-optimal trajectory planning
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-022-08796-y

Effective motion control could achieve the accurate positioning and fast movement of industrial robotics to improve industrial productivity significantly. Time-optimal trajectory optimization (TO) is a great concern in the motion control of robotics, which could improve motion efficiency by providing high-speed and reasonable motion references to motion controllers. In this study, a new general time-optimal TO strategy, the second-order continuous polynomial interpolation function (SCPIF) combined with the particle swarm optimization with cosine-decreasing weight (CDW-PSO) subject to kinematic and dynamic limits, successfully optimizes the movement time of the PUMA 560 serial manipulator. The SCPIF could be used to generate the second-order continuous movement trajectories of six joints in joint space based on the assigned positions and time intervals. The CDW-PSO algorithm could further search for the optimal movement time subject to the limits of the angular displacement, angular velocity, angular acceleration, angular jerk, and joint torque of the manipulator. Two numerical experiments are conducted to illustrate the generalization ability of the CDW-PSO algorithm. The advantage of the CDW would be reflected by comparing with the random weight (RW), the constant weight (CW), and the linearly decreasing weight (LDW), respectively, in each experiment. The experimental results show that the CDW-PSO algorithm would perform better than the RW-PSO, CW-PSO, and LDW-PSO algorithms in terms of the convergence rate and quality of the convergent solution. The proposed time-optimal TO strategy would be applied to all types of manipulators while the optimized trajectories could be incorporated in the motion controllers of the actual manipulators due to considering the kinematic and dynamic limits.